| dc.description.abstract | In manufacturing plants, the combination of production scheduling and preventive maintenance
is critical for schedule development. Complex production processes at different levels are
frequently included in systems consisting of many machines with different characteristics.
Problems that integrate multiple calendars frequently require the solution of more than one
problem at a time. Many essays have been written to address this issue, but most of them only
address a small portion of the complexity of real-world systems. Furthermore, the methods
proposed in previous articles do not appear to be effective in resolving this problem. This thesis
paper proposes a mixed integer linear programming (MILP) model to integrate production
scheduling and preventive maintenance in multi-machine systems more efficiently. The goal is
to lower the total cost as much as possible, which includes nine sub-costs: early and late penalty
costs, parts holding costs, assembly holding costs, assembly costs, production costs, setup costs,
delivery costs, production idle time costs, and maintenance costs. In Phase 1, the MILP model
is run using CPLEX. Then, in Phase 2, the results from Phase 1 are processed and plotted into
a Gantt chart using Python software. Gantt charts are used to show the optimal schedule of
production and preventive maintenance activities in a visually appealing, easy-to-understand,
and manageable format. The MILP model is the most effective method for large-scale cases
with a large amount of data | en_US |
